Research On Multi-camera Objects Detecting And Tracking

The visual tracking is a basic research topic in the field of computer vision, but also a very challenging research direction. In the current real life, visual tracking technology has been widely applied in various fields, including video surveillance, military engineering, traffic management, intelligent robots and human-computer interaction and so on, and has high value of academic research and application.Single-camera visual tracking system has many unresolved issues, including the target occluding, the limitation of camera field of vision, can not be omnibearing tracking and so on, but multi-camera tracking system can well overcome these problems. Therefore, Multi-camera object detection and tracking is becoming a hot research. Based on previous research, the paper focus on how to improve the accuracy of target identification between multi-camera, and how to reduce data transmission and computation in the overall system, ensuring the accurate target tracking.First of all, the paper analyzes the target recognition problem between cameras in the field of multi-camera tracking, and puts forward a new method. The method introduces the feature of target distance into the homography-based technique of identification. As the plane homography constraints can not impact the distance between targets, adding the distance feature can effectively improve the target identification accuracy between different cameras. The Experimental results show that the new method can improve the accuracy of target identification, when the homography-based recognition algorithm is added the distance feature.In order to effectively reduce data transmission and computation in the multi-camera tracking system, the paper also proposes a new tracking algorithm based on the optimal camera selection, and evaluates the performance of this algorithm from the theoretical analysis and experiment. The Experimental results show that the algorithm can effectively reduce the transmission and computation of the tracking system, but not loss of tracking accuracy.